Profile millions of records in seconds. Find missing values, format inconsistencies, and violations. Get completeness scores, distributions, and quality metrics before cleaning.
Assess Your Data Health.avif)
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Profile all fields for completeness and uniqueness. See columns with missing data and unexpected format variations.
Find relationships between datasets. Detect data type mismatches and schema conflicts across all your data sources.
Analyze value distributions and frequency patterns. Get min, max, mean, median statistics for every numeric field.
“As part of the journey we’ve gone through with Matchlogic, we’re becoming more data-first, moving from assumption to assurance around data quality.”
Analyze every field across millions of records simultaneously for completeness, uniqueness, and validity. Get statistical distributions, frequency patterns, and format analysis. One scan reveals all quality issues systematically.
Identify format patterns and validate against expected rules automatically. Character analysis shows text composition, statistical analysis reveals numeric distributions. Pattern recognition flags anomalies and violations instantly.
Get min, max, mean, median, mode for numeric fields. See frequency distributions for categorical data. Character analysis reveals text patterns. Every field gets comprehensive statistical breakdown for informed decisions.
Schedule profiling runs hourly, daily, or triggered by data loads. Track quality trends automatically. Get alerts when completeness drops or violations spike. Monitor data quality continuously without manual intervention.
See your data's reality in seconds. matchlogic analyzes every field across all systems simultaneously, revealing completeness scores, format patterns, and statistical distributions. Know exactly which fields are unreliable and why.
Get completeness percentages for every field instantly. See which columns are mostly empty and which systems skip required data consistently.
Discover how values actually appear across your systems. Pattern analysis shows format variations, character distributions, and validation violations for every field.
Identify which fields are 40% empty and killing match accuracy. Know which systems skip required data and what percentage of records are incomplete.
Find connections between datasets and dependencies. Discover where data types mismatch and schemas conflict across different data sources.
Get hard metrics on actual data quality. matchlogic calculates completeness percentages, format consistency rates, and statistical distributions for every field. Track quality trends to prove improvement or catch degradation early.
Every field gets scored for completeness, format consistency, and uniqueness. Know which fields are reliable for matching and which need cleaning first.
See which systems produce the cleanest data and which create chaos. Compare quality scores across CRM, ERP, and warehouses to find your problem sources.
Get probability scores showing likelihood of duplicates. High-risk records get flagged before they create customer confusion or compliance failures.
Automated scans flag PII in wrong fields, incomplete required data, and audit risks. Get compliance scores that prove your data meets regulatory standards.
Get comprehensive profiling reports instantly. matchlogic generates completeness scores, statistical summaries, and pattern analysis for every field. Export quality metrics as CSV, JSON, or detailed reports. Filter results by field type, quality threshold, or system source.
Red zones show duplicate clusters and quality failures at a glance. Click to drill into specific records. See patterns humans miss in traditional reports.
Visualize how values spread across your data. See if customer IDs cluster suspiciously or if date fields have impossible values. Spot anomalies instantly.
Watch quality scores change over time. See when duplicates spike, which systems drift, and whether cleanup efforts actually work. Prove ROI with data.
Schedule profiling to run hourly, daily, or triggered by data loads. matchlogic monitors quality continuously without manual intervention. Get alerts when duplicate rates exceed thresholds or quality drops.
Embed profiling directly in your data pipelines. Every new data load gets profiled automatically. Catch quality issues before they hit production systems.
Compare today's profile against last week, last month, or last year. See if data quality improves or decays. Prove the value of your cleanup initiatives.
First profile revealed 40% missing data and format chaos we never suspected. Helped us fix issues before migration.
Profiling showed our 'clean' vendor data was 28% duplicates. Found $3M in duplicate payments in minutes.
We profile before every project now. Reveals quality issues that would break analytics. Saves weeks of cleanup.
Not assumptions or guesses. Upload your data and see completeness scores, patterns, and quality metrics instantly.
Identify Errors In Your Data
Profiling instantly shows exact duplicate counts, missing data percentages, format variations, and quality scores for every field. You'll see where "McDonald's" has 20 different spellings, which systems create the most duplicates, and which fields are 40% empty. Visual heat maps highlight problem zones across all your systems simultaneously.
matchlogic profiles 10 million records in under 8 minutes, maintaining the same speed whether scanning thousands or billions of records. The engine analyzes every field, identifies patterns, calculates quality scores, and generates visual reports without performance degradation.
Most companies discover 25-35% duplicate records they never knew existed. The average first-time profile uncovers thousands of hidden duplicates costing real money. Profiling reveals duplicates hiding behind misspellings, abbreviations, and format differences your team would never catch manually.
Yes - profiling gives you potential duplicate percentages and risk scores before you write any matching rules. You'll know exactly how many likely duplicates exist, where they cluster, and which fields have the variations causing problems. This helps you configure match rules based on your actual data patterns, not guesswork.
Yes - schedule profiling hourly, daily, weekly, or triggered by data loads via API. Embed profiling directly in your data pipelines to catch quality issues before they hit production. Set threshold alerts for when duplicate rates exceed limits or quality scores drop. Automated profiling keeps constant watch without manual intervention.
Profiling automatically flags PII in wrong fields, incomplete required data, and audit risks. It identifies records missing mandatory fields, catches format violations, and documents quality scores for compliance reporting. Every profile run creates audit trails showing your data quality status and improvement trends - turning audit panic into audit proof.
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